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Some financial perspectives on comparative costs of capital.

*J. Fred Weston is Professor Emeritus of Managerial Economics and Finance, Anderson Graduate School of Management, University of California at Los Angeles, CA. He also is an Associate Editor of this Journal. The author thanks Clement G. Krouse for considerable guidance in preparation of this article.

1 See footnotes and references at end of text.

Empirical studies of international cost of capital comparisons have taken two related form. One is to compare weighted average costs of capital (WACC) for samples across economies. Sample WACC comparisons may be subject to error because the cost of capital measures may not be applied to appropriate definitions of operating cash flows whose qualities, time-growth patterns, and risk may differ. Comparisons of riskless rates such as yields on government securities ignore relevant risk differences. No financially derived competitive advantage is likely to exist with: (1) no net tax or subsidy differences, (2) capital market and economic integration.

MUCH HAS BEEN written on whether firms in some countries have a lower cost of capital than firms in other countries. This article first reviews the cost of capital measurement methodologies employed in prior studies of financially derived competitive advantage (FDCA). The problems with these studies motivate use of an alternative methodology based on widely accepted models of asset pricing in the literature of financial economics.(1)


One major challenge confronting measurement procedures is whether the samples of firms being compared have similar technology and product market opportunities. Otherwise differences may arise from nonfinancial characteristics rather than financial. In addition to distinguishing between operational and financial sources of competitive advantage, other difficult measurement problems also must be resolved.

The traditional approach to making comparisons of the cost of capital for firms is the weighted average cost of capital (WACC) method measured by:

k = WACC = K[.sub.b] (1 - T) L + K[.sub.s] (1 - L) (1) where k = WACC = weighted average cost of capital

k[.sub.b] = cost of debt

k[.sub.s] = cost of equity

T = corporate tax rate

L = debt at market value divided by value of a firm (V)

In implementing the WACC method it is also traditional to employ a discounted cash flow (DCF) procedure. The combined DCF/WACC method poses difficult measurement problems, as suggested by Table 1. The first issue is whether to use before-tax or after-tax measures. The correct procedure is to start with comparable before-tax operating cash flows, then compare the ratios of the capitalized values to the after-tax cash flows. Differences in types of taxes, kinds of deductions, and administrative policies and practices are reflected in the before-tax and after-tax calculations.

Measuring the cost of debt must take into account a wide variety of factors to establish comparability in samples across countries. The measurement problems are even more difficult for cost of equity comparisons. The time framework for measurements also poses dilemmas. Theory requires that the analysis be forward looking - based on expectations. The available data are mainly historical.

More problems are confronted in calculating the weights. Previous studies of the costs of capital across countries have mainly used historical book weights. But it is an error not to take market values into account. In practice, managements for different combinations of reasons may have some target range as an objective. These subtleties are difficult to encompass in large scale studies.

To illustrate the nature of the difficulties, we shall describe the problems of measuring the cost of equity capital in the DCF/WACC approach. In concept, the cost of equity is the appropriate yield to maturity, k, that equates the expected cash flow streams to the observed price in Equation (2).

P [identical to] V [identical to] CF[.sub.1]

---------- +

(1 + k) CF[.sub.2] CF[.sub.3] CF[.sub.n] ---------- + ---------- + ... + ---------- (2) (1 + k)[.sup.2] (1 + k)[.sup.3] (1 + k)[.sup.n] Where P [identical to] V = price or value

CF = the expected cash flow to equity at each date

k = the cost of equity capital

Prices for publicly traded firms can be observed. The operating cash flows to equity are the expected cash flows for some planning horizon. But the expected cash flows can take a variety of time patterns. Some studies of FDCA assume that the cash flows in the numerator are constant and continue to perpetuity. Under this assumption the cash flows are priced by Equation (3).

P = (CF[.sub.o])/k (3)

Such studies solve Equation (3) for k and use the earnings-price ratio or the dividend-price yield as the measure of the cost of equity capital. Other studies of the cost of capital across countries make less restrictive assumptions about the pattern of cash flows. A model erroneously called the "standard finance valuation model" assumes that the cash flows in the numerator of Equation (2) are measured by earnings (E) or dividends (D) and grow at a constant rate, g. The resulting valuation expression is Equation (4).

P = E/(k - g) (4) The earnings-price ratio is sometimes still used as the measure of the cost of equity capital. However, this is clearly incorrect since k, the cost of equity capital, in the constant growth model is:

k = E/P + g (4a) In Equation (4) g cannot be greater than k. Nor can the growth rate for an individual firm or group of firms exceed the growth rate of the economy to perpetuity. Hence some assume g to be the same as the growth rate in the economy. But individual firms are likely to have time patterns of varying levels of growth.

The correct way to deal with the above problems in estimating the cost of equity is to solve for k in Equation (2) as set forth by Malkiel [1979], taking differences of risk into account. The theoretically correct procedure would require much more effort than previous studies. Some past estimates of comparative capital costs find that U.S. firms have a positive FDCA, others negative; some find small positive or negative FDCAs, some large.(2) The diverse results suggest that measurement errors may account for apparent differences and that actual FDCA differences are not known.


In contrast to the DCF/WACC studies, others focus on U.S. macroeconomics policies in comparison to those of other countries said to produce a negative FDCA for U.S. firms. But the link between the theory and evidence has not been established. Writers differ on the national economic policies to be changed, which is to be expected since many macroeconomic factors can affect FDCA as shown in Table 2.

Because many factors could produce FDCAs, positive or negative, it is not enough to assert: (1) Government policies XYZ can affect FDCA. (2) Some data show FDCA. (3) Ergo, FDCA exists and is produced by policies XYZ. The logic is weak at each step. Even if FDCA existed, economic analysis would have to relate it back to specific national policies, excluding other possible explanations. What may really be involved is differences in macroeconomic philosophies among the writers. Further, if FDCA does not exist, the syllogism collapses.

These difficulties stimulate consideration of an approach stemming from developments in the modern theory of financial economics. This research tests for the possibility of FDCA without directly measuring it.

Capital Market integration

The Nobel prize in economics in 1990 was awarded to three financial economists for their work in developing the theory of capital market asset pricing.(3) One result of the Markowitz-Miller-Sharpe contributions was the Capital Asset Pricing Model (CAPM), which measures the required return to assets and securities by a risk-free rate plus a risk premium calculated by the product of the market price of risk times a measure of the non-diversifiable risk of the returns to the individual asset or security. Empirical tests used groups of portfolios to calculate risk-adjusted costs of capital. A subsequent more general development is the Arbitrage Pricing Theory (APT) [Ross, 1976; Roll and Ross, 1980]. APT holds that the returns to assets or securities are determined by multiple factors, such as (1) market returns, (2) unanticipated inflation, (3) unanticipated changes in risk premia or in (4) twists in the yield curve. An illustration of the APT is Equation (5).

k = r[.sub.f] + [Lambda][.sub.1][Beta][.sub.1] + [Lambda][.sub.2][Beta][.sub.2] + [Lambda][.sub.3][Beta][.sub.3] + [Lambda][.sub.4][Beta][.sub.4] (5) where k is the expected return for the security; r[.sub.f] is the riskfree rate; [Beta][.sub.1], through [Beta][.sub.4] are the assets' covariation (firm specific risks or sensitivities) with the factors; and [Lambda][.sub.1], through [Lambda][.sub.4] are the "prices" of these risks or the market risk-premia rates. Some illustrative numbers with the [Lambda][.sub.s] in parens:

k = .07 + (.05).4 + (.02).5 + (.04).1 + (.03).2 = 11% (5a)

To facilitate graphical exposition, we postulate that the several APT sensitivity factors are encompassed by a composite risk factor designated beta ([Beta]) measured along the horizontal axis of Figure 1, which portrays an asset pricing line in which dollars are the numeraire currency.

An issue is whether the dollar risk-free and risk-premia rates (jointly) are equal for the (u) securities of the U.S. as compared with other countries indicated by the letter j in Figure 1. One possibility provides a perspective on the DCF/WACC studies. Figure I illustrates a different required return for the u country securities as compared with the i country securities. There is only one asset pricing line, capital market integration obtains between the countries, but firms in the j country have a lower required cost of capital. The reason is that they have less risk. In any given country, different firms face different risks and would therefore have different required rates of return or costs of capital. But this is not FDCA.

Two recent studies have tested for capital market integration using APT. In addition to local risk-free securities, Cho et al. [1986] used monthly return observations (using dollars as the numeraire currency) for sixty U.S. securities and fifty-five Japanese securities during the eleven-year period 1973-83. Risk-free and risk-premia rates for five risk factors were derived from these data, separately for the U.S. and Japanese securities. A statistical test that the dollar risk-free and risk-premia rates (jointly) were equal for securities of the different countries was rejected, indicating a lack of capital market integration and the possibility of FDCA during this period. Gultekin et al. [1989] tested the equality of risk-free and risk-premia rates during two separate four-year sample periods, 1977-80 and 1981-84, The distinction between periods was intended to isolate any effects of the Japanese capital market liberalization reforms of late 1980. The Gultekin et al. observations were weekly security returns, again calculated using dollars as the numeraire currency, of 110 U.S. and 110 Japanese firms along with the local risk-free rates. While they found statistically significant differences for risk-free and risk-premia rates during the earlier period, no such differences were evident during the later 1981-84 period, implying no FDCA after 1980.

Economic integration

Solnik [1983] has shown that it is not enough that portfolios of U.S. and other country securities have the same r[.sub.f] and [Lambda][.sub.s] when calculated in one numeraire currency. A further requirement for no FDCA is that when the other currency is used as the numeraire, the same real r[.sub.f] and [Lambda][.sub.s] are obtained. When these equalities hold so that dollar and yen (for example) pricing equations are identical on a real basis, economic integration holds. When the interest rate parity (IRP) and purchasing power parity (PPP) conditions hold (approximately), the real risk-free rates among countries are equal. For economic integration, the [Lambda][.sub.s] must also be equal.

Empirical work to date has not performed the further test of using the foreign currency as a numeraire as well as the domestic, but some inferential evidence is available. Using long-term government bond yields, Bernheim and Shoven [1986] estimated the 1971-82 real interest-rate differential to be between 0.23 and 0.93 percent, depending on the method by which the inflation rate was measured. They also noted an increase of this differential to about 2 percent (average) during the 1983-85 period. Using similar long-term bond data from the first quarters of 1986-88, French and Poterba [1989] estimated the differential at just 0.58 percent. Some tentative, indirect evidence from Hamao [1988] suggests that the risk premia differences across countries are negligible. These results are consistent with economic integration and no FDCA. Studies which use inflation-adjusted interest rate differences between the U.S. and other countries as evidence of FDCA fail to recognize the implications of (approximate) parity conditions.


There are potentially serious biases in studies using the DCF/WACC methodology to discern a financially derived competitive advantage (FDCA) between U.S. and other firms. The principal sources of this bias are a neglect of differences in the time-growth profiles of equity cash flow streams and their riskiness.

While not conclusive, the available empirical evidence suggests the following: U. S. and other capital markets have been integrated since 1981. If there are no significant tax or subsidy differences among countries, studies that appear to show differences in cost of capital between U.S. and other countries may be reflecting measurement errors or failure to recognize the implications of economic integration.


1 For a more complete treatment of the topics in this paper see, C. G. Krouse and J. F. Weston, "Financially Derived Competitive Advantage: An Overview of Key Issues," ms., 1/31/91.

2 A. Ando and A. Auerbach, 1985, 1988a, 1988b, 1990; D. Bernheim and J. Shoven, 1986; G. Hatsopoulis and S. Brooks, 1986; K. French and J. Poterba, April 1989; R. McCauley and S. Zimmer, Summer 1989; J. Frankel, 1990.

3 H. M. Markowitz, Portfolio Selection: Efficient Diversification of Investments, New York: John Wiley and Sons, 1959; M. H. Miller, "Debt and Taxes," Journal of Finance, 32, May 1977, pp. 261-275; W. F. Sharpe, "Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk," Journal of Finance, September 1964.


Ando, A., and A. Auerbach, "The Corporate Cost of Capital in the U. S. and Japan: A Comparison," in J. Shoven, ed., Government Policy Towards Industry in the United States and Japan, Cambridge: Cambridge University Press, 1985, pp. 21-49.

__________, "The Corporate Cost of Capital in Japan and the United States: A Comparison," in J. Shoven, ed., Government Policy Towards Industry in the United States and Japan, Cambridge University Press, 1988a.

__________, "The Cost of Capital in the United States and Japan: A Comparison," Journal of the Japanese and International Economics, 2, 1988b, pp. 134-158.

__________, "The Cost of Capital in Japan: Recent Evidence and Further Results," NBER Working Paper No. 3371, 1990.

Bernheim, D., and J. Shoven, "Taxation and the Cost of Capital," unpublished manuscript, Stanford University, 1986.

Cho, D.; C. Eun; and L. Senbet, "International Arbitrage Pricing Theory: An Empirical Investigation," Journal of Finance, 41, 1986, pp. 313-329.

Frankel, Jeffrey A., "Japanese Finance: A Survey," NBER Working Paper No. 3156, 1990.

French, K., and J. Poterba, "Are Japanese Stock Prices Too High?" CRSP Seminar on the Analysis of Prices, University of Chicago, April 1989.

Gultekin, M.; N. Gultekin; and A. Penati, Capital Controls and International Capital Market Segmentation: The Evidence from the Japanese and American Stock Markets," Journal of Finance, 44, 1989, pp. 849-869.

Hamao, Y., "An Empirical Examination of the Arbitrage Pricing Theory Using Japanese Data," Working Paper, University of California, San Diego, 1988.

Hatsopoulis, George N., and Stephen H. Brooks "The Gap in the Cost of Capital: Causes, Effects, and Remedies," in R. Landau and Dale Jorgensen, eds., Technology and Economic Policy, Cambridge: Ballinger, 1986, Chapter 12, pp. 221-280.

Malkiel, Burton G., "The Capital Formation Problem in the United States," The Journal of Finance, 34, May 1979, pp. 291-306.

McCauley, R., and S. Zimmer, "Explaining International Differences in the Cost of Capital," FRBNY Quarterly Review, Summer 1989, pp. 7-28.

Roll, R. W., and S. A. Ross, "An Empirical Investigation of the Arbitrage Pricing Theory," The Journal of Finance, 35, December 1980, pp. 1073-1103.

Ross, S. A., "The Arbitrage Theory of Capital Asset Pricing," Journal of Economic Theory, 13, December 1976, pp. 341-360.

Solnik, B., "International Arbitrage Pricing Theory," Journal of Finance, 38, 1983, pp. 449-457.
 Table 1
 Measurement of Component Costs of Capital
 I. Before Tax or After Tax
 1. Corporate taxes
 2. Personal taxes
 3. Capital gains taxes
 4. Deductibility of payments
 5. Deductions in measuring taxable income
 6. Tax administration policies and practices
 II. Cost of Debt
 1. Government vs. corporate
 2. By debt ratings
 3. Default probabilities
 4. Short-term vs. long-term
 5. Unsecured vs. secured
 6. By industry?
 7. Samples of firms?
 8. Risks of firms
 9. Product-market mixes
 10. Financial leverage ratios
 11. Coverage of financial charges
 12. Institutional vs. individual holders
 13. Growth rates of firms
 14. Covenants of borrowing arrangements
 15. Maturity structure of debt
 16. Duration patterns of assets and claims
 III. Cost of Equity
 1. Level of risk-free rate
 2. Slope of Security Market Line
 3. Systematic factors affecting equity risk
 4. Growth rates of assets, earnings, etc.
 5. Models of time-growth patterns of cash flows
 a. No growth
 b. Constant growth
 c. Alternative constant growth rates
 (1) Economy
 (2) Industry
 (3) Firms
 d. Periods of super or sub-growth
 6. Alternative cash return or dividend patterns
 7. Internal vs. external equity financing
 8. Treatment of flotation costs
 IV. Time Frame of Measurements
 1. Historical
 2. Current
 3. Anticipatory
 4. Average
 Table 2
 Policies and Variables Affecting FDCA
I. Macroeconomic Policies
 A. Budget surplus or deficit
 B. Tight or easy money policy
 C. Social security policy
 D. Tax policies
 1. ITC
 2. Accelerated depreciation
 3. Reserves against losses
 4. Administrative policies
 E. Spending policies and patterns
 1. Defense
 2. Welfare
 3. Productive
 4. Unproductive
 F. Industrial policy
 1. Direct and indirect research subsidies
 2. Direct and indirect effects of tax policies on
 individual industries
 3. Executive or legislative pressures
 G. Governmental and institutional environments
 H. Wage policy
 1. Gain sharing
 2. Wage changes in relation to CPI and productivity
 3. Management of human resources
 4. Capital/labor ratios
II. Macroeconomic Variables
 A. Savings rates
 B. Investment rates
 C. Price behavior
 D. Rates of productivity change
 E. Quality of the educational system
 1. Primary
 2. Secondary
 3. Graduate
 4. Relations between education, business, and
 F. Investment opportunities
 G. Growth rates of the economies and individual segments
 H. Rates of innovation in the economy
 I. Land prices
 J. Exchange rates
 K. Instability of economic, political, and social
 1. Instability of GNP levels
 2. Instability of interest rates
 3. Instability of foreign exchange rates
 4. Instability of government regimes
 5. Ability of government to make decisions
 6. Leadership qualities of top level government policy

Figuration Omitted.
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Author:Weston, J. Fred
Publication:Business Economics
Date:Apr 1, 1991
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